serving-llms-vllm
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
65
78%
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Critical
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tessl review fix ./backend/cli/skills/ml-inference/vllm/SKILL.mdSecurity
1 critical severity finding. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
E006: Malicious code pattern detected in skill scripts.
What this means
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
Why it was flagged
The documentation repeatedly recommends enabling trusted-remote-code and binding the server/metrics to public interfaces and third-party model repositories, which creates high-risk vectors for remote code execution and supply-chain compromise (RCE/backdoor and supply-chain attack patterns).
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required runtime workflow (“Run batch inference” / “Production API deployment” calling `llm.generate(prompts, ...)` or serving OpenAI-compatible `/v1` chat completions) ingests user-supplied prompt text into the model context; this can be outsider free text if requests/prompt files come from outside parties.
- Repository
- synthetic-sciences/openscience
- Commit
3a6c3a9
- Audited
- Security analysis
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